Truly autonomous learning systems that autonomously and accurately identify essential features across multiple domains (i.e., general AI) is still science fiction, but dynamic, continuous learning models are useful in interpreting alternative data in novel ways.Read Blog
Truly autonomous learning systems that autonomously and accurately identify essential features across multiple domains (i.e., general AI) is still science fiction, but dynamic, continuous learning models are useful in interpreting alternative data in novel ways.
M&A in the Biotech space started strong for 2019 with the buyout of Celgene and Loxo. A high level of confidence for deal making in this sector means it is perfect for generating stock trading ideas. Investors are paying close attention to rumors so they know which stocks are good to buy right now!
M&A analysts have relied on vetted sources to identify potential M&A market chatter. Traditional paradigms, have become ineffective and the number of rumors published by low-popularity M&A news sources greatly outnumbers that of high-popularity sources. Is There Informational Alpha in these Sources?
Trepidation as investors look ahead this week as 4 major Canadian banks report their earnings for the fiscal fourth. The high cost of real estate, coupled with the OECD’s large household debt burden, mean that Canadian consumers are especially vulnerable to economic shocks.
Accrete will be attending the NeuData Alternative Data Summit in London, where the future of investment data is decided. Prashant Bhuyan, CEO, shares his insights on key topics that will be discussed including the future of alternative data in investment decisions and the problem of the ‘black box’.
The application of AI in automating cognitive processes is on the rise. The launch of J.P. Morgan’s new retail trading platform underscores this trend, and highlights what is rapidly becoming the new normal. The question is, can AI live up to the hype and deliver excessive gains for investors?
Having access to unique data sets were once enough to generate alpha! Gaining an edge in today’s markets requires extracting deeper insights even the savviest investors are finding it difficult to achieve. Using intelligent cognitive automation investors can within minutes start generating alpha.
Accurate prediction is at the core of making profitable trading decisions in the M&A space. However, seeing into the future is no simple task because there are too many sources from which M&A rumors emanate. We’ve found that you can very successful identifying deals before they are announced!
Fintech is evolving at a breakneck pace, and financial analysts are being left behind! Once the favorite sons of Wall Street banks & investment firms, they are now in fear of being replaced by the latest 'toy' on the market: AI. Learn why AI isn't replacing Analysts, but improving their findings!
Sibos 2018 is the global financial services networking event of the year and connects more than 8,000 financial professionals from across the industry. For those who are traveling to the event and have some spare time, we have put together an alternative guide to Sydney for you.
If our relationships with our AI tools are to induce better decision making over the long-term, we must trust the reasoning behind the insights offered by the AI. Without attribution of output to reason, there’s no way for humans to benchmark and validate whether or not the AI truly understands..
Human analysts are all subject to irrational and unconscious bias. Why do some portfolio managers succumb to ‘The Disposition Effect’ while others reach a heightened level of self-awareness. What is the solution to eliminating unconscious bias and long-term market under-performance?… A.I. ?
M&A activity remains strong into the third quarter so how can investors profit from this robust M&A space? With the right strategy, mergers & acquisitions can be a remunerative space. Being aware of chatter surrounding a company helps investors locate opportunistic trades, modify positions, and more
Errant tweets plunge stocks into the red. Irrational bias compounds and can trigger mass market movements, outpacing the speed of human biological processing capabilities. Human intelligence is no longer adequate to make sense of the financial markets alone, it requires something more.
The burden of transforming raw digital data into actionable intelligence is far too great for even the savviest of fund managers. Investors are innovating and using cognitive systems to support human decision-making. AI can derive optimal solutions, for humans to predict future outcomes
With the explosion in unstructured data a fundamental problem for humans is our ability to make sense of it all; the biological brain isn't growing as fast as the data. Within the context of financial markets, information overload causes significant problems for investors looking for excessive gains